Seasonal variations of outdoor air pollution and factors driving them in the school environment in rural Bhutan

A quantitative understanding of outdoor air quality in school environments is crucial given that air pollution levels inside classrooms are significantly influenced by outdoor pollution sources. To date, only a handful of studies have been conducted on this important topic in developing countries. The aim of this study was to quantify pollutant levels in the outdoor environment of a school in Bhutan and assess the factors driving them. Measurements were conducted for 16 weeks, spanning the wet and dry seasons, in a rural school in Bhutan. PM10, PM2.5, particle number (PN) and CO were measured daily using real-time instruments, while weekly samples for volatile organic compounds (VOCs), carbonyls and NO2 were collected using a passive sampling method. Overall mean PM10 and PM2.5 concentrations (µg/m3) were 27 and 13 for the wet, and 36 and 29 for the dry season, respectively. Only wet season data were available for PN concentrations, with a mean of 2.56 × 103 particles/cm3. Mean CO concentrations were below the detection limit of the instrumentation for the entire measurement period. Only low levels of eight VOCs were detected in both the wet and dry seasons, which presented different seasonal patterns in terms of the concentration of different compounds. The notable carbonyls were formaldehyde and hexaldehyde, with mean concentrations (µg/m3) of 2.37 and 2.41 for the wet, and 6.22 and 0.34 for the dry season, respectively. Mean NO2 cocentration for the dry season was 1.7 µg/m3, while it was below the detection limit of the instrumentation for the wet season. The pollutant concentrations were associated with a number of factors, such as cleaning and combustion activities in and around the school. A comparison with other school studies showed comparable results with a few of the studies, but in general, we found lower pollutant concentrations in the present study.

An empirical analysis of the factors and measures of Enterprise Architecture Management success

Enterprise Architecture Management (EAM) is discussed in academia and industry as a vehicle to guide IT implementations, alignment, compliance assessment, or technology management. Still, a lack of knowledge prevails about how EAM can be successfully used, and how positive impact can be realized from EAM. To determine these factors, we identify EAM success factors and measures through literature reviews and exploratory interviews and propose a theoretical model that explains key factors and measures of EAM success. We test our model with data collected from a cross-sectional survey of 133 EAM practitioners. The results confirm the existence of an impact of four distinct EAM success factors, ‘EAM product quality’, ‘EAM infrastructure quality’, ‘EAM service delivery quality’, and ‘EAM organizational anchoring’, and two important EAM success measures, ‘intentions to use EAM’ and ‘Organizational and Project Benefits’ in a confirmatory analysis of the model. We found the construct ‘EAM organizational anchoring’ to be a core focal concept that mediated the effect of success factors such as ‘EAM infrastructure quality’ and ‘EAM service quality’ on the success measures. We also found that ‘EAM satisfaction’ was irrelevant to determining or measuring success. We discuss implications for theory and EAM practice.

Prevalence and risk factors of refractive errors among schoolchildren in Shiraz, Iran

Purpose: To determine the prevalence and risk factors of refractive errors among schoolchildren in Shiraz, Iran. Methods: In a cross-sectional study, using random cluster sampling, 3065 Shiraz schoolchildren were selected in this study. The participants totaled 2683; 1872 elementary and middle school and 811 high school students. For the primary and middle schoolchildren, cycloplegic refraction and for the high school students, non-cycloplegic autorefraction was measured. Myopia, defined as spherical equivalent (SE) refraction -0.50 diopter (D) or worse, hyperopia as SE +2.00D and +0.50D or more for cycloplegic and noncycloplegic refractions respectively, and astigmatism as cylinder -0.75D or worse. Results: The prevalence of refractive errors in elementary and middle school students was: myopia 4.35 % (95% confidence interval (CI), 2.89 -5.81), hyperopia 5.04 % (95%CI, 3.49 -6.58) and astigmatism 11.79 % (95%CI, 10.21 -13.38). For high school students, these rates were 22.4 % (95%CI, 18.44 -26.36), 10.52 % (95%CI, 6.75 -14.29) and 20.99% (95%CI, 16.55 -25.44), respectively.The prevalence of myopia increased with age in primary and middle school students (OR=1.15, 95% CI, 0.98 to1.33, p=0.073). Conclusions: The result of this study indicated a relatively low prevalence of refractive errors among schoolchildren in Shiraz according to the protocol by "Refractive Error Study in Children" (RESC) in other investigations.